Scanning software creates duplicate files primarily to preserve multiple versions or variations of a scanned document during the capture and processing workflow. This can happen intentionally, such as when a user scans the same physical document multiple times to improve quality or selects different save formats (like PDF and JPG). It can also occur unintentionally due to automatic naming conventions that don't guarantee uniqueness, software saving temporary files improperly, or misconfigured workflows that trigger redundant scanning steps. Unlike deliberate backups, these are often unintended file copies cluttering storage.

Common scenarios include a document management system saving the original scan alongside an OCR-processed text-searchable version, effectively creating two related but distinct files. Similarly, users editing a scanned document directly within an app might find separate files for the raw scan and the edited copy, or rescanning might generate files named "Scan(1).pdf", "Scan(2).pdf" using incremental numbering conventions seen in scanners or mobile scanning tools.

While duplicates can offer accidental version history, they significantly waste storage space and cause confusion in file management. This inefficiency can lead to data overload, making it harder to locate the correct document version. Future solutions leverage AI-driven file management tools to intelligently identify and consolidate true duplicates, improving efficiency. Recognizing why duplicates form helps users configure scanning workflows better and implement cleanup strategies.